Not entirely unlike dogs socializing via their nether regions, Facebook’s latest idea is to wirelessly sniff out people around you and make friend suggestions based on what it finds. Only it’s slightly more intrusive than how dogs do it.

The patent, which got the go-ahead last month, is like the current People You May Know feature sprouting legs and trotting up to random strangers who have the awesome good luck of finding themselves in your proximity.

Does Facebook need yet more technology for this? It’s not as if it’s not already adept – to put it lightly – at rummaging through our everything to find ties that bind.

Take, for example, the interview published by Fusion editor Kashmir Hill a few years ago: it was with a father who attended a gathering for suicidal teens. The father was shocked to discover that following the highly sensitive meeting one of the participants duly appeared in his People You May Know feed.

The two parents hadn’t exchanged contact information (one way Facebook suggests friends is to look at your phone contacts). The only connection the two appeared to have was being in the same place at the same time, and thus their smartphones being in the same room.

Hill said that Facebook’s response gave her “reportorial whiplash”: first, it suggested that location data was used by People You May Know if it wasn’t the only thing that two users have in common, then said that it wasn’t used at all, and then finally admitted that it had been used in a test late in 2015 but was never rolled out to the general public.

Introduced in 2008, People You May Know has been both remarkably accurate and extremely opaque about how it makes friend suggestions. As in, “the networks that you are a part of, mutual friends, work and education information, contacts imported using the Friend Finder,” and the murky kitchen junk drawer of “many other factors.”

The feature is designed to help users discover new connections, be they long-forgotten school chums or colleagues. Of course, besides helping people to build out their own networks, it’s also darn handy when it comes to enabling Facebook to build a treasure trove of valuable data about us and the people with whom we associate.

That daisy-chaining analysis has enabled people like National Security Agency (NSA) agents to pull the communications of innocent people into far-reaching surveillance dragnets that snare friends of friends of actual targets, as was shown in leaked documents from Edward Snowden.

Patterns of movement

At any rate, to make its friend-suggesting, data-vacuuming technologies all the more data-grabby, the new patent describes a method of using the devices of Facebook app users to identify wireless signals – including Bluetooth, Z-Wave or Zigbee, NFC or PAN communications – from other users’ devices.

The patent says that the Facebook mobile app might be designed to make suggestions based on how physically close the new “friend” might be, plus how often the two people have met and how long the meetings have lasted. Or even, say, patterns of when users have likely had meetings. Imagine the possibilities: if you take the subway at a given time each day, for example, the guy who always sits across from you could pop up in your suggested friends list.

Outfitted with the technology described in the patent, the Facebook app could record not only how often devices are close to one another and meeting time and duration, but also their movement patterns. Relying on a device’s gyroscope and accelerometer to analyze movement patterns could, for example, help Facebook determine whether the two users went for a run together, strolled down the street together, or are habitually two sardines packed into that subway car together.

We’ll make them all blips on our radar, Facebook says:

In one embodiment, the movement pattern can include at least one of a stationary pattern, a walking pattern, a running pattern, or a vehicle-riding pattern.

In one embodiment, a graphical element representing the second user can be presented on a display element of the computing system. The graphical element can be moved on the display element based on a locational proximity between the computing system and a source of the second wireless communication. The locational proximity can be determined using the signal strength data associated with the second wireless communication.

Facebook’s algorithm would crunch all this data to figure out the likelihood of two users having actually met, even if they’re not Facebook friends already and have no other virtual connections. If that algorithm finds people’s patterns of “meeting” are “sufficiently significant,” they could receive nudges about possibly becoming friends.

This all would come in handy when you meet somebody at a cocktail party or convention, say, forget to ask for their contact information, and don’t apparently share mutual connections, Facebook suggests:

If, for example, the first user meets the second user but forgets to obtain the second user’s contact information and does not apparently share any mutual connections with the second user, it can be challenging or inefficient for the first user to search for and find the second user within the social networking service. These and other similar concerns can reduce the overall user experience associated with using social networking services.

You know who else might appreciate sniffing out people wirelessly? Cyberstalkers.

Oh, and police. This could be a good thing: a few years ago, a victim identified an armed robber after Facebook suggested him as a friend to his victim. Nothing like being held at knifepoint to get “proximity” bells ringing!

It could also be yet another investigative tool brought to law enforcement courtesy of Facebook, willingly or otherwise – the platform recently scolded police for using fake accounts to snoop on citizens.

It could be any or all of those things. For now, it’s just a patent. But given Facebook’s history with suggesting friends and what it’s already admitted about trialling such proximity-based technologies, it sounds like we’ll likely see it rolled out sooner, rather than later.